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Agent skill

Hunting Advanced Persistent Threats

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Proactively hunts for Advanced Persistent Threat (APT) activity within enterprise environments using hypothesis-driven searches across endpoint telemetry, network logs, and memory artifacts.

Apache-2.0Auto-check passedSecurity

Install Hunting Advanced Persistent Threats

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill hunting-advanced-persistent-threats -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills hunting-advanced-persistent-threats --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hunting-advanced-persistent-threats .claude/skills/hunting-advanced-persistent-threats && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hunting-advanced-persistent-threats
GitHub stars
34k
Token cost
~1.7k tokens
SKILL.md length
686 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Proactively hunts for Advanced Persistent Threat (APT) activity within enterprise environments using hypothesis-driven searches across endpoint telemetry, network logs, and memory artifacts.

  • Works in 5 steps: Develop Hunt Hypothesis → Identify Required Data Sources → Execute Hunts with Velociraptor or osquery → …
  • Conducting scheduled threat hunting cycles
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 2 more sections
  • Runs Python scripts from its folder

What it does

Hunting Advanced Persistent Threats is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Proactively hunts for Advanced Persistent Threat (APT) activity within enterprise environments using hypothesis-driven searches across endpoint telemetry, network logs, and memory artifacts. Use when conducting scheduled threat hunting cycles, investigating anomalous behavior flagged by UEBA, or validating that known APT TTPs are not present in the environment. Activates for requests involving MITRE ATT&CK, Velociraptor, osquery, Zeek, or threat hunting playbooks.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Security operations. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Conducting scheduled threat hunting cycles
  • Investigating anomalous behavior flagged by UEBA
  • Validating that known APT TTPs are not present in the environment

Example prompts

  • “/hunting-advanced-persistent-threats”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Develop Hunt Hypothesis
  2. Identify Required Data Sources
  3. Execute Hunts with Velociraptor or osquery
  4. Analyze Results and Pivot
  5. Document and Operationalize Findings

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • attack.mitre.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hunting Advanced Persistent Threats loads about 1.7k tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 126 tokens; SKILL.md has 686 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~126
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 686 words, ~1,692 tokens.

Download SKILL.mdSave it as .claude/skills/hunting-advanced-persistent-threats/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
hunting-advanced-persistent-threats
description
Proactively hunts for Advanced Persistent Threat (APT) activity within enterprise environments using hypothesis-driven searches across endpoint telemetry, network logs, and memory artifacts. Use when conducting scheduled threat hunting cycles, investigating anomalous behavior flagged by UEBA, or validating that known APT TTPs are not present in the environment. Activates for requests involving MITRE ATT&CK, Velociraptor, osquery, Zeek, or threat hunting playbooks.
domain
cybersecurity
subdomain
threat-intelligence
tags
MITRE-ATT&CK, threat-hunting, APT, Velociraptor, osquery, Zeek, TTP, NIST-CSF, EDR
version
1.0.0
author
mahipal
license
Apache-2.0
d3fend_techniques
File Metadata Consistency Validation, Application Protocol Command Analysis, Identifier Analysis, Content Format Conversion, Message Analysis
nist_csf
ID.RA-01, ID.RA-05, DE.CM-01, DE.AE-02
mitre_attack
T1591, T1592, T1593, T1589, T1005

Hunting Advanced Persistent Threats

When to Use

Use this skill when:

  • Conducting proactive threat hunting sprints (typically 2–4 week cycles) based on newly published APT intelligence
  • A UEBA alert or anomaly detection system flags behavioral deviations warranting deeper investigation
  • A peer organization or ISAC sharing partner reports active APT compromise and you need to validate your own exposure

Do not use this skill as a substitute for incident response when a confirmed breach is in progress — escalate to IR procedures (NIST SP 800-61).

Prerequisites

  • EDR platform with telemetry retention (CrowdStrike Falcon, Microsoft Defender for Endpoint, or SentinelOne) covering 30+ days
  • Access to MITRE ATT&CK Navigator for hypothesis development
  • Network flow data (NetFlow, Zeek, or Suricata logs) in a queryable SIEM
  • Threat hunting platform or query interface (Velociraptor, osquery fleet, or Splunk ES)

Workflow

Step 1: Develop Hunt Hypothesis

Select a threat actor relevant to your sector using MITRE ATT&CK Groups (https://attack.mitre.org/groups/). Review the group's known TTPs mapped to ATT&CK techniques. Example hypothesis: "APT29 (Cozy Bear) uses spearphishing with ISO attachments (T1566.001) and living-off-the-land binaries (T1218) — test for unusual mshta.exe and rundll32.exe parent-child relationships."

Document hypothesis using the Threat Hunting Loop framework: hypothesis → data collection → pattern analysis → response.

Step 2: Identify Required Data Sources

Map each ATT&CK technique to required log sources using the ATT&CK Data Sources taxonomy:

  • Process creation (T1059): Windows Security Event 4688 or Sysmon Event ID 1
  • Network connections (T1071): Zeek conn.log, NetFlow, EDR network telemetry
  • Registry modifications (T1547): Sysmon Event ID 13, Windows Security 4657
  • Memory injection (T1055): EDR memory scan telemetry, Volatility output

Verify log coverage using ATT&CK Coverage Calculator or a custom data source matrix.

Step 3: Execute Hunts with Velociraptor or osquery

Velociraptor VQL hunt for unusual PowerShell execution:

vql
SELECT Pid, Ppid, Name, CommandLine, CreateTime
FROM pslist()
WHERE Name =~ "powershell.exe"
AND CommandLine =~ "-enc|-nop|-w hidden"

osquery for persistence via scheduled tasks:

sql
SELECT name, action, enabled, path
FROM scheduled_tasks
WHERE action NOT LIKE '%System32%'
AND enabled = 1;

Splunk SPL for lateral movement via PsExec:

spl
index=windows EventCode=7045 ServiceFileName="*PSEXESVC*"
| stats count by ComputerName, ServiceName, ServiceFileName
Step 4: Analyze Results and Pivot

For each anomaly identified, pivot across dimensions:

  • Temporal: Did this occur before or after known IOC timestamps?
  • Host: How many endpoints exhibit this behavior?
  • User: Is the associated account a service account, privileged user, or regular user?
  • Network: Does the host communicate with external IPs not in baseline?

Apply the Diamond Model (adversary, capability, infrastructure, victim) to structure findings.

Step 5: Document and Operationalize Findings

If hunting reveals confirmed malicious activity, activate IR procedures. If hunting reveals a gap (hunt found nothing but data coverage was insufficient), document the coverage gap and remediate.

Convert successful hunt queries into SIEM detection rules using Sigma format for portability across platforms.

Show full SKILL.md (274 more words)Show less

Key Concepts

TermDefinition
TTPTactics, Techniques, and Procedures — adversary behavioral patterns as defined in MITRE ATT&CK
Diamond ModelAnalytical framework with four vertices (adversary, capability, infrastructure, victim) used to structure intrusion analysis
Living-off-the-Land (LotL)Attacker technique using legitimate OS tools (PowerShell, WMI, certutil) to evade detection
UEBAUser and Entity Behavior Analytics — ML-based detection of anomalous behavior baselines
SigmaOpen standard for SIEM-agnostic detection rule format, analogous to YARA for network/log detection
Hunt HypothesisA testable prediction about adversary presence based on threat intelligence and environmental knowledge

Tools & Systems

  • Velociraptor: Open-source DFIR platform with VQL query language for scalable endpoint hunting across thousands of systems
  • osquery: SQL-based OS instrumentation framework for real-time endpoint telemetry queries
  • MITRE ATT&CK Navigator: Web-based tool for visualizing ATT&CK coverage and technique prioritization
  • Zeek (formerly Bro): Network traffic analyzer producing structured logs (conn, dns, http, ssl) suitable for hunting
  • Elastic Security: EQL (Event Query Language) enables sequence-based hunting for multi-stage attack patterns
  • Sigma: Detection rule format with translators for Splunk, QRadar, Sentinel, and Elastic

Common Pitfalls

  • Confirmation bias: Starting a hunt expecting to find something and interpreting benign data as malicious. Document null results — they validate controls.
  • Insufficient data retention: Many APT techniques require 90+ days of log history to identify slow-and-low patterns. Default retention periods are often too short.
  • Hunting without baselines: Cannot identify anomalies without knowing normal. Spend time on baseline documentation before hunting.
  • Query performance impact: Broad queries against production SIEM during business hours can degrade analyst workflows. Schedule intensive hunts during off-peak hours.
  • Ignoring false positives systematically: Track false positive rates per query. Queries with >80% FP rate should be refined or retired before operationalization.

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/hunting-advanced-persistent-threats of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

Compare with similar skills

Hunting Advanced Persistent Threats next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hunting Advanced Persistent Threats compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Hunting Advanced Persistent Threats this skillmukul975/Anthropic-Cybersecurity-Skills34k—~1.7kAutomated safety check: PassApache-2.0
Security Alert Triageelastic/agent-skills5921 repos~3.5kAutomated safety check: NotesApache-2.0
Kubernetes Network Security Auditkubeshark/kubeshark12k—~7.3kAutomated safety check: NotesApache-2.0
Security Detection Rule Managementelastic/agent-skills5921 repos~3.9kAutomated safety check: NotesApache-2.0
Chaitin CLIchaitin/chaitin-cli115—~15kAutomated safety check: NotesGPL-3.0
GatesNebulock-Inc/agentic-threat-hunting-framework388—~12kAutomated safety check: PassMIT

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Categories

Questions about Hunting Advanced Persistent Threats

What does Hunting Advanced Persistent Threats do?

Proactively hunts for Advanced Persistent Threat (APT) activity within enterprise environments using hypothesis-driven searches across endpoint telemetry, network logs, and memory artifacts. Hunting Advanced Persistent Threats is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Proactively hunts for Advanced Persistent Threat (APT) activity within enterprise environments using hypothesis-driven searches across endpoint telemetry, network logs, and memory artifacts.

When should I use Hunting Advanced Persistent Threats?

Hunting Advanced Persistent Threats fits situations like: conducting scheduled threat hunting cycles; investigating anomalous behavior flagged by UEBA; validating that known APT TTPs are not present in the environment.

How do I install Hunting Advanced Persistent Threats in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill hunting-advanced-persistent-threats -a claude-code`. Or copy the skill folder (skills/hunting-advanced-persistent-threats in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/hunting-advanced-persistent-threats in your project. Claude Code loads it when a task matches its description.

How do I install Hunting Advanced Persistent Threats in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill hunting-advanced-persistent-threats -a codex`. Or copy the skill folder (skills/hunting-advanced-persistent-threats in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/hunting-advanced-persistent-threats in your project. Codex loads it when a task matches its description.

Can I use Hunting Advanced Persistent Threats in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill hunting-advanced-persistent-threats -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hunting-advanced-persistent-threats, .gemini/skills/hunting-advanced-persistent-threats, .github/skills/hunting-advanced-persistent-threats and .opencode/skills/hunting-advanced-persistent-threats in your project.

What does Hunting Advanced Persistent Threats need to run?

Going by SKILL.md and its folder, Hunting Advanced Persistent Threats needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Hunting Advanced Persistent Threats access the network?

SKILL.md names 1 domain. As links in the text: attack.mitre.org. This is read from the text; nothing was executed.

Is Hunting Advanced Persistent Threats safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Hunting Advanced Persistent Threats use?

Hunting Advanced Persistent Threats is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hunting Advanced Persistent Threats use?

About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 529 tokens, read only when the agent opens those files.

What are the alternatives to Hunting Advanced Persistent Threats?

Skills that share tags, products or a category with Hunting Advanced Persistent Threats: Security Alert Triage (elastic/agent-skills, 592 stars), Kubernetes Network Security Audit (kubeshark/kubeshark, 12k stars), Security Detection Rule Management (elastic/agent-skills, 592 stars) and Chaitin CLI (chaitin/chaitin-cli, 115 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hunting Advanced Persistent Threats?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.